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Neural networks for robotics : an engineering perspective / Nancy Arana-Daniel, Alma Y. Alanis, Carlos Lopez-Franco.

By: Contributor(s): Material type: TextPublisher: Boca Raton : CRC Press, Taylor & Francis Group, 2019Description: xvii, 209 pages : illustrations ; 25 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780815378686
Subject(s): DDC classification:
  • 629.8/92632 ARA
LOC classification:
  • TJ211.35 .A73 2019
Summary: The book offers the reader the insight on artificial neural networks for giving a robot a high level of autonomy tasks such as navigation, object recognition, and clustering, with real-time implementations. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures to solve different kinds of problems encountered in autonomous navigation and object recognition problems. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control-- Provided by publisher.
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Holdings
Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
Permanent Reference Nagananda International Institute for Buddhist Studies(NIIBS) 629.892632 ARA (Browse shelf(Opens below)) 08313 Not for loan 08313

"A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc."

Includes bibliographical references and index.

The book offers the reader the insight on artificial neural networks for giving a robot a high level of autonomy tasks such as navigation, object recognition, and clustering, with real-time implementations. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures to solve different kinds of problems encountered in autonomous navigation and object recognition problems. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control-- Provided by publisher.

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